A BAYESIAN PANEL VECTOR AUTOREGRESSION TO ANALYZE THE IMPACT OF CLIMATE SHOCKS ON HIGH-INCOME ECONOMIES

• 成果类型: Article
• 署名作者: Huber, Florian; Krisztin, Tamas; Pfarrhofer, Michael
• 署名单位: Salzburg University; International Institute for Applied Systems Analysis (IIASA); University of Vienna
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/22-AOAS1681
• 发表日期: 2023
• 页码: 1543-1573
• 关键词: agricultural commodity prices; food-prices; finite mixtures; monetary-policy; euro area; oil price; models; volatility; Heterogeneity; transmission

摘要

In this paper we assess the impact of climate shocks on futures markets for agricultural commodities and a set of macroeconomic quantities for multiple high-income economies. To capture relations among countries, markets, and climate shocks, this paper proposes parsimonious methods to estimate high-dimensional panel vector autoregressions. We assume that coefficients associated with domestic lagged endogenous variables arise from a Gaussian mixture model while further parsimony is achieved using suitable globallocal shrinkage priors on several regions of the parameter space. Our results point toward pronounced global reactions of key macroeconomic quantities to climate shocks. Moreover, the empirical findings highlight substantial linkages between regionally located shocks and global commodity markets.